45336 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| | 45336 Zip Code | Ohio | U.S. |
| Total Housing Units | 59, 100% | 4,570,015 | 116,211,092 |
| Utility Gas | 1, 1.69%, see rank | 66.89% | 48.85% |
| Bottled, Tank, or LP Gas | 28, 47.46%, see rank | 5.26% | 4.86% |
| Electricity | 16, 27.12%, see rank | 22.05% | 36.68% |
| Fuel Oil, Kerosene, etc. | 6, 10.17%, see rank | 2.60% | 5.86% |
| Coal or Coke | 0, 0.00%, see rank | 0.07% | 0.12% |
| Wood | 8, 13.56%, see rank | 2.02% | 2.12% |
| Solar Energy | 0, 0.00%, see rank | 0.02% | 0.05% |
| Other Fuel | 0, 0.00%, see rank | 0.72% | 0.47% |
| No Fuel Used | 0, 0.00%, see rank | 0.37% | 1.00% |
ACS 2008-2012 data
| | 45336 Zip Code | Ohio | U.S. |
| Total Housing Units | 55, 100% | 4,555,709 | 115,226,802 |
| Utility Gas | 1, 1.82%, see rank | 67.58% | 49.42% |
| Bottled, Tank, or LP Gas | 22, 40.00%, see rank | 5.46% | 5.03% |
| Electricity | 23, 41.82%, see rank | 21.02% | 35.51% |
| Fuel Oil, Kerosene, etc. | 7, 12.73%, see rank | 2.90% | 6.46% |
| Coal or Coke | 0, 0.00%, see rank | 0.08% | 0.12% |
| Wood | 2, 3.64%, see rank | 1.98% | 2.08% |
| Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
| Other Fuel | 0, 0.00%, see rank | 0.67% | 0.43% |
| No Fuel Used | 0, 0.00%, see rank | 0.30% | 0.90% |
US Census 2000 data
| | 45336 Zip Code | Ohio | U.S. |
| Total Housing Units | 37, 100% | 4,445,773 | 105,480,101 |
| Utility Gas | 0, 0.00%, see rank | 68.80% | 51.22% |
| Bottled, Tank, or LP Gas | 15, 40.54%, see rank | 6.14% | 6.52% |
| Electricity | 9, 24.32%, see rank | 18.29% | 30.35% |
| Fuel Oil, Kerosene, etc. | 13, 35.14%, see rank | 4.70% | 8.97% |
| Coal or Coke | 0, 0.00%, see rank | 0.07% | 0.14% |
| Wood | 0, 0.00%, see rank | 1.07% | 1.68% |
| Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
| Other Fuel | 0, 0.00%, see rank | 0.65% | 0.39% |
| No Fuel Used | 0, 0.00%, see rank | 0.25% | 0.69% |
* ACS stands for U.S. Census American Community Survey. According to the U.S. Census, if the date is a range, you can interpret the data as an average of the period of time.
